@inproceedings{dearden-baron-2018-lancaster,
    title = "{L}ancaster at {S}em{E}val-2018 Task 3: Investigating Ironic Features in {E}nglish Tweets",
    author = "Dearden, Edward  and
      Baron, Alistair",
    editor = "Apidianaki, Marianna  and
      Mohammad, Saif M.  and
      May, Jonathan  and
      Shutova, Ekaterina  and
      Bethard, Steven  and
      Carpuat, Marine",
    booktitle = "Proceedings of the 12th International Workshop on Semantic Evaluation",
    month = jun,
    year = "2018",
    address = "New Orleans, Louisiana",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/S18-1096/",
    doi = "10.18653/v1/S18-1096",
    pages = "587--593",
    abstract = "This paper describes the system we submitted to SemEval-2018 Task 3. The aim of the system is to distinguish between irony and non-irony in English tweets. We create a targeted feature set and analyse how different features are useful in the task of irony detection, achieving an F1-score of 0.5914. The analysis of individual features provides insight that may be useful in future attempts at detecting irony in tweets."
}